智能电网中面向隐私保护的数据聚合算法

随着智能电网(SG)的迅速发展，其安全和效率受到广泛关注。在SG中，居住区域内多个智能电表(SM)设备将感测数据传输至控制中心，使得用户数据需经过一些中间节点才到达控制中心。而通过挖掘用户相关数据(URD)，攻击者能够窃取用户的习惯和行为，因此，需要保护用户的隐私。为此，提出面向隐私保护的数据聚合(PPDA)算法。PPDA算法利用群位置隐私(GLP)掩饰由SM产生的数据，并利用Paillier加密系统对用户数据进行保护。此外，PPDA算法无需任何安全信道。仿真结果表明，提出的PPDA算法能够防御偷听攻击和勾结攻击，并控制了计算开销。

A privacy-preserving data aggregation algorithm in Smart Grid networks

In Smart Grids(SG), measured user data in Smart Meter(SM) in residential area are sent to Control Center(CC) passing through a few intermediate nodes. Hence, privacy preserving of user data is one of the biggest challenges in smart grid researches because the habits and behaviors of users can be disclosed by data mining the User-Related Data(URD). A Privacy-Preserving Data Aggregation(PPDA) algorithm is proposed. In PPDA algorithm, the Group Location Privacy(GLP) approach is taken advantage to mask fine-grained user data generated by SMs, and Paillier encryption system is utilized to preserve the user data privacy. The proposed protocol does not need any secure channel. The security and performance analysis shows that the proposed approach is secure against eavesdropping attack and collusion, and its computational overhead is acceptable compared with that of the previous works.